Attitudes and Practices Among Pediatric Oncologists Regarding End-of-Life Care: Results of the 1998 American Society of Clinical Oncology Survey
Bibliographic record
Abstract
PURPOSE: In 1998, the American Society of Clinical Oncology (ASCO) surveyed its membership to assess the attitudes, practices, and challenges associated with end-of-life care of patients with cancer. In this report, we summarize the responses of pediatric oncologists and the implications for care of children dying from cancer. METHODS: The survey consisted of 118 questions, covering eight categories. All ASCO members in the United States, Canada, and the United Kingdom were mailed a survey, which was completed by 228 pediatric oncologists. Predictors of particular attitudes and practices were identified using stepwise logistic regression analysis. Potential predictors were age, sex, religious affiliation, importance of religious beliefs, recent death of a relative, specialty, type of practice (rural or urban, academic or nonacademic), amount of time spent in patient care, number of new patients in the past 6 months, and number of patients who died in the past year. RESULTS: Pediatric oncologists reported a lack of formal courses in pediatric palliative care, a strikingly high reliance on trial and error in learning to care for dying children, and a need for strong role models in this area. The lack of an accessible palliative care team or pain service was often identified as a barrier to good care. Communication difficulties exist between parents and oncologists, especially regarding the shift to end-of-life care and adequate pain control. CONCLUSION: Pediatric oncologists are working to integrate symptom control, psychosocial support, and palliative care into the routine care of the seriously ill child, although barriers exist that make such comprehensive care a challenge.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".